Self-optimizing wireless network

ABSTRACT

Optimizing a plurality cell sites or sectors in a wireless netwrok including receiving network data regarding a plurality of cell sites or sectors; determining a critical zone in which communication is degraded; determining best neighbor cell sites or sectors among the neighbor cell sites or sectors associated with the critical cell sites or sectors; determining if the critical cell sites or sectors in the critical zone have available resources for achieving a desired improvement in communications; determining if the best neighbor cell sites or sectors have available resources for achieving the desired improvement in communications; and altering wireless network parameters of the critical cell sites or sectors, or the best neighbor cells sites or sectors for achieving the desired improvment in communications.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.12/580,604, filed Oct. 16, 2009, and entitled “Self-Optimizing WirelessNetworks,” which is incorporated herein by reference in its entirety.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention generally relates to planning and optimization fora wireless network. In particular, the present invention relates to asystem that monitors network performance, and makes changes to networkparameters to enhance performance.

2. Description of the Related Art

Network planning of a wireless network relies on static approaches forsite locations and dimensioning of the radio resources to meet specifiedtraffic demand at busy hours. In a wireless network, a large number ofbase stations (i.e., cell sites) can be served by one or more antennas.The base station hardware will send a radio frequency signal to theantennas, which will typically be placed on towers or buildings. Eachantenna (i.e., sector) serves end-users located in a coverage area.Within a coverage area different types of services can be provided(e.g., voice and data services).

The coverage area provided by an antenna is determined by antennaconfigurations and input power to the antenna. Antenna configurationsare, for example, the antenna horizontal pointing direction, the azimuthbeamwidth of the antenna, and downtilt angle of the antenna. Modifyingthese antenna configurations will change the area the antenna is serving(i.e., coverage area) and possibly areas served by other surroundingantennas.

Input power (i.e., the power sent from the base station or cell site) tothe antenna will also affect the coverage of the antenna as well as theinterference that impacts the coverage areas of neighboring antennas.For example, if an antenna's input power is increased, the coverage areaof the antenna may increase as well, thereby causing interference to thecoverage area of a neighboring antenna and affecting the quality ofservice in that neighboring antenna's coverage area. When the radiosignal quality is better, due to good network planning and performance,higher data rates for voice and data services can be achieved withoutconsuming too many radio power resources.

Network planning and optimization is a process of finding the bestconfiguration of the wireless network so as to maximize performance ofthe network. This process typically starts with an already workingwireless network, and then calculations and analysis are done byengineers using software and hardware tools and extensive simulationsfor the network. Once a better configuration is determined, the newconfiguration will be manually implemented in the network.

However, network planning and optimization consumes a high amount ofhuman resources. In addition, it is a lengthy process which is done onlywhen needed or periodically with long periods between implementation. Inaddition, because this process is manual and lengthy, it is conductedwith low frequency, which results in leaving the network or parts of thenetwork without optimization for long periods of time. Thus, networkresource usage is not maximized and unused available network resourcesresult in significant revenue loss. Finally, quality of service isdegraded, which affects the end user's overall customer satisfaction.

Therefore, it would be useful to implement an automated system fornetwork planning and optimization that adjusts radio resources andnetwork parameters to maximize overall network performance.

SUMMARY OF THE INVENTION

An embodiment of the invention is directed to a method for optimizing aplurality cell sites/sectors in a wireless network. The method includesreceiving network data regarding a plurality of cell sites/sectors, eachcell site/sector corresponding to a coverage area for providingcommunications in a wireless network; evaluating the network data todetermine if communications provided by the plurality of cellsites/sectors has been degraded; and determining a critical zone inwhich communication is degraded. The critical zone includes criticalcell sites/sectors needing improved communications and neighbor cellsites/sectors corresponding to the critical cell sites/sectors.

The method also includes determining best neighbor cell sites/sectorsamong the neighbor cell sites/sectors; determining if the critical cellsites/sectors in the critical zone have available resources forachieving a desired improvement in communications; determining if thebest neighbor cell sites/sectors have available resources for achievingthe desired improvement in communications, when it is determined thatthe critical cells sites do not have adequate available resources forachieving the desired improvements in communications; altering wirelessnetwork parameters of the critical cell sites/sectors or the bestneighbor cells sites for achieving the desired improvement incommunications; and determining if the desired improvement incommunications has been achieved by altering the wireless networkparameters.

Altering wireless network parameters of the critical cell sites/sectorsor the best neighbor cell sites/sectors are performed continuously untilthe desired improvement in communications in the wireless network isachieved.

An embodiment of the invention is also directed to program recorded on acomputer-readable storage medium for optimizing a plurality cellsites/sectors in a wireless network. The program causes a computer toexecute optimizing steps comprising receiving network data regarding aplurality of cell sites/sectors; evaluating the network data todetermine if communications provided by the plurality of cellsites/sectors has been degraded; and determining a critical zone inwhich communication is degraded.

The program also causes the computer to perform the steps of determiningbest neighbor cell sites/sectors among the neighbor cell sites/sectors;determining if the critical cell sites/sectors have available resourcesfor achieving a desired improvement in communications; determining ifthe best neighbor cell sites/sectors have available resources forachieving the desired improvement in communications, when it isdetermined that the critical cells sites do not have adequate availableresources; altering wireless network parameters of the critical cellsites/sectors or the best neighbor cells sites for achieving the desiredimprovement in communications; and determining if the desiredimprovement in communications has been achieved by altering the wirelessnetwork parameters.

An embodiment of the invention is also directed to a system foroptimizing a plurality cell sites/sectors in a wireless network. Thesystem comprising an optimization apparatus that monitors network dataassociated with a plurality of cell sites/sectors and performsalterations to network parameters wireless network; at least onecontroller configured to perform data communications with theoptimization apparatus; a least one base station configured to performdata communication with the at least one controller; at least onecontrollable antenna configured to perform data communication with theat least one base station and a plurality of subscribers distributed ina plurality of coverage areas; and a dynamic load balancing apparatusconfigured to perform data communication with the optimization apparatusand the at least one controllable antenna.

An embodiment of the invention is also directed an apparatus foroptimizing a plurality cell sites/sectors in a wireless networkcomprises a communication interface; at least one processor; and amemory, the memory storing a optimizing program for causing theapparatus to perform optimizing operations.

BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings, like reference numbers generally indicate identical,functionally similar and/or structurally similar elements. Embodimentsof the invention will be described with reference to the accompanyingdrawings, wherein:

FIG. 1 illustrates a system for optimizing of network parameters in awireless network in accordance with an embodiment of the invention;

FIG. 2 illustrates a method for optimizing of network parameters in awireless network in accordance with an embodiment of the invention;

FIG. 3 illustrates a method for determining a critical zone requiringoptimizing of network parameters in accordance with an embodiment of theinvention;

FIG. 4 illustrates a method for determining a best neighbor cell inaccordance with an embodiment of the invention; and

FIG. 5 illustrates an apparatus for optimizing of network parameters ina wireless network in accordance with an embodiment of the invention.

Additional features are described herein, and will be apparent from thefollowing description of the figures.

DETAILED DESCRIPTION OF THE INVENTION

In the description that follows, numerous details are set forth in orderto provide a thorough understanding of the invention. It will beappreciated by those skilled in the art that variations of thesespecific details are possible while still achieving the results of theinvention. Well-known elements and processing steps are generally notdescribed in detail in order to avoid unnecessarily obscuring thedescription of the invention.

In the drawings accompanying the description that follows, often bothreference numerals and legends (labels, text descriptions) may be usedto identify elements. If legends are provided, they are intended merelyas an aid to the reader, and should not in any way be interpreted aslimiting.

FIG. 1 is a system for optimizing of network parameters in a wirelessnetwork in accordance with an embodiment of the invention. Inparticular, the wireless network 100 illustrated in FIG. 1 includes anetwork optimization apparatus 101. The wireless network 100 refers toany type of computer network that is wireless, and is commonlyassociated with a telecommunications network whose interconnections areimplemented without the use of wires such as with electromagnetic waves,such as radio waves or the like as a carrier. The basic components ofthe wireless network 100 include the network optimization apparatus 101,one or more controllers 102, and one or more base stations 103 (i.e.,cell sites) for supporting data communications between subscribersdistributed throughout coverage areas provided by the wireless network100 via antennas 105 (i.e., sectors), a network database 110, and adynamic load balancing apparatus 104.

It should be understood by one of ordinary skill in the art that theconnections between the network optimization apparatus 101 and the oneor more network controllers 102, the dynamic load balancing apparatus104 and the network database 110 can be wireless, wired or a combinationof wireless and wired. Similarly, it should be understood by one ofordinary skill in the art that the connections between the one or morecontrollers 102 and the one or more base stations 103 can be wireless,wired or a combination of wireless and wired.

As seen in FIG. 1, the network optimization apparatus 101 receivesnetwork statistics and the current network configurations from thenetwork database 110 related to the wireless communication system 100for assisting in the monitoring and optimization performed. The networkstatistics may include, but are not limited to, key performanceIndicators (KPIs). An example of a KPI is the dropped calls rate, whichis the ratio between the failed calls and the total number of callsrequested. Another network statistic is the capacity of the network.Capacity can be measured by total number of calls and/or the amount ofdelivered data in bits or the throughput (overall data rate) in case ofdata calls.

A network parameter important to consider when performing networkoptimization is the number of handovers of end-user equipments betweendifferent sectors. User equipment has serving sectors, as the user movesbetween the coverage areas of different sectors, the serving sector willbe changed as other sectors may have better signal quality. In a softhandover, the user will have more than one serving sector in the sametime as the signal quality of different sectors are close to each other.The number of handovers between different sectors could be used asindicator of how close sectors are to each other, or an indicator to thedependency between different sectors.

Another network parameter important to consider when performing networkoptimization is a neighbor list. The neighbor list includes all thepotential neighbors for a sector, and it may include neighbor prioritiesas well. A potential neighbor is a neighbor sector which may providedservices to mobile equipment as part of a handover operation when themobile equipment is traveling between different coverage areas. Theneighbor lists of the sectors which are serving the mobile equipment maybe arranged to construct one list to be sent to the mobile equipment.The mobile equipment will use this longer list to search for additionalpotential neighbors for handover operations.

The network optimization apparatus 101 can be a server or other similarcomputer device capable of executing an algorithm for performingoptimization of network parameters in wireless network 100. A moredetailed discussion of the structure of the network optimizationapparatus 101 is noted below with reference to FIG. 5.

The controllers 102 illustrated in FIG. 1 are, for example, base stationcontrollers (BSC), which are part of the wireless system infrastructurethat control one or more of the base stations 103 and the correspondingcoverage areas provided by the base stations 103. A plurality ofsubscribers (not shown) is distributed within the coverage areas forparticipating in wireless data communications provided by the wirelessnetwork 100 via the antennas 105. The subscribers have user equipmentthat may include various types of fixed, mobile, and portable two wayradios, cellular telephones, personal digital assistants (PDAs), orother wireless networking devices.

Each coverage area behaves as an independent sector serving its own setof subscribers. For fixed wireless systems, such as IEEE802.16-2004,each coverage area can be used by a single base station 103 or pluralityof base stations 103 operating each on a different frequency channel.For mobile systems, subscribers of a single coverage area are served bya single base station 103 that can be a single frequency channel forIEEE802.16e-2005 (or UMTS or 1x-EVDO Rev. B and C) or multiple frequencychannels that can be supported by IEEE802.16m (or UMTS or 1xEVDO Rev. Band C).

As illustrated in FIG. 1, the dynamic load balancing apparatus 104 mayalso receive subscriber statistics. The dynamic load balancing apparatus104 includes an algorithm that analyzes the data related to the wirelessnetwork 100 and sends control signals to the antennas and/or basestations 103 for altering or shaping the coverage areas. The loadbalancing algorithm may cluster users based on their instantaneouslocations or by means of heuristic approaches; collects statistics tovalidate previous users clustering decisions and/or predicting newtraffic patterns; and continuous learns and adaptively shapes thecoverage areas and alters network parameters as the environment ortraffic density changes with time. As seen in FIG. 1, network statisticsreceived by the network optimization apparatus can also be provided tothe dynamic load balancing apparatus 104.

FIG. 2 illustrates a method for optimizing of network parameters in awireless network in accordance with an embodiment of the invention. Byway of example, the self-optimization apparatus 101 can execute analgorithm stored therein for performing optimization operations.

Prior to optimizing operations on the wireless network, there needs tobe an identification of zones (i.e., critical zones) in the wirelessnetwork requiring optimization. Identification of a critical zone willbe discussed in more detail with reference to FIG. 3. The zones will beidentified as a group of cell sites/sectors on which the optimizationwill be preformed. Identification of the zones needing optimization canbe based on the critical cell site/sector that has performance problemsbased on some criteria. Additionally, different areas of the wirelessnetwork can be evaluated using different criteria. The criteria can bebased on one or more performance metrics of the wireless network over apast period of time and/or one or more predicted performance metrics.These performance metrics can be based on previous performance andconfigurations as well as previous traffic and predicted traffic.

A performance metrics can be for a voice/data service for all servicesor for weighted services; and can be for the critical cell site/sectoronly or for the entire critical zone or for overall weighted performancebetween different cell sites/sectors. The performance metrics can alsobe for a specific time slot in a day or over a few days, for all timesor for overall weighted times, and can be changed automatically ormanually between different sets of performance metrics based on somecriteria. For the criteria that changes automatically between differentperformance metrics sets, the criteria can be based on past or predictedconfigurations, performance metrics and/or traffic.

For each critical cell site/sector needing optimization, a local zonewill be identified as the set of the neighbor cell sites/sectors basedon some criteria, which can also be based on one or more performancemetrics. For example, the performance metric can be based on thecells/sectors dropped call rate (DCR), which has exceeded certaindropped call rate threshold over certain window of time. The performancemetric can also be calculated across specific time slots in differenttime frames. For example, Mondays to Fridays, Mondays only or Mondays toFridays morning hours.

The local zone may contain only the critical cell/sector, directneighbors of the critical site/sector or the direct neighbors and theneighbors of neighbors or additional levels of neighbors. For each groupof overlapped local zones, critical zones will be identified as theunion of these overlapped zones. The final critical zones may notinclude overlapping zones. The zone identification process is runcontinuously to identify new zones needing optimization.

The old and newly identified critical zones can also be ranked based onthe criteria used in identifying the critical zones. Based on theavailable computing resource in the optimization system as well as therank of the zones, one or more of the critical zones will be chosen foroptimization in serial, parallel or both. When a critical zone isselected for optimization, the optimization will be conductedcontinuously as performance metric data and configurations arrive to theoptimization apparatus, as shown in FIG. 2.

Referring now to FIG. 2, in step 201, the self-optimization apparatus101 monitors the wireless network. The self-optimization apparatus 101monitors performance after implementing recommended configurationmodifications. In step 202, the network optimization apparatus 101determines if new network data has been received. If not, then thewireless network will continue to be monitored, as in step 201.Otherwise, in step 203, the network optimization apparatus 101 willdetermine whether the operating conditions of the cell sites/sectors inthe zones have been degraded based on the new data received. Thecriteria can be based on one or more of performance metrics similar tothose noted above for indentifying the zones. For example, theperformance metric can be based on the DCR of cells/sectors in the zonesor capacity increases. If performance in the zone has degraded, then instep 204, the previous recommended configuration modifications areremoved until the best previous operation state is achieved, and in step220 the self-optimization process ends.

However, if the operating conditions of the zones have not been degradedbased on the previous recommended configuration modifications, then instep 205 it is determined if an observation window has been reached. Anobservation window is simply a specified time period such a number ordays. For example, the optimization apparatus may determine that it isnecessary to monitor network data for a certain numbers of days. If anobservation window has not been reached, then the wireless network willcontinue to be monitored, as in step 201. However, once the observationwindow has been reached, performance metrics can be calculated andcompared to performance metrics before the previous recommendedconfiguration modifications or compared to the first KPIs. An algorithmwill evaluate the KPIs after the previous observation windows have beenreached and find the configurations which resulted in the best KPIs. Ifthe current network performance is better, then the previous recommendedconfiguration modifications will be accepted. However, if performance isdegraded, then the previous recommended configuration modifications areremoved.

Thus, after the observation window has been reached in step 205 then, instep 206 it is determined if the operating conditions of the cellsites/sectors in the zones have been degraded. If a degraded conditionis determined in step 206, then in step 204 the previous recommendedconfiguration modifications are removed until the best previousoperation state is achieved, and in step 220 the self-optimizationprocess ends. If in step 206 it is determined that the operatingconditions of the cell sites/sectors in the zones have not beendegraded, then in step 207 a critical hour is determined.

The critical hour may be the specific time a zone suffers from a highlydegraded condition. In step 208, it is determined if the criticalcell/sector has enough available resources for the critical hour. Forexample, the determination of available resources could be based on, butis not limited to, the number of calls which could be additionallyserved by the critical cell site/sector; how many calls could beaveragely served by any used hardware; or how many calls could beaveragely served by the unused power. If the number of calls isdetermined to be less or greater than a preset/dynamic threshold, thenit can be determined if the critical cell site/sector has adequateavailable resources to address the degraded condition.

If it is determined that the cell site/sector has available resources,then the previous recommended configuration modifications are removed(in step 204) and, for example, load balancing techniques can be used toaddress the degradation condition in the zone instead. The optimizationprocess is then ended in step 220. If the cell site/sector does not haveadequate available resources, then in step 209 a best neighbor cellsite/sector is determined for assisting in addressing the degradedcondition. For example, from the critical cell sectors/site neighborlist, the top neighbors are determined based on which neighborssectors/sites have a high number of handovers with the critical cellsite/sector; and/or the neighbor cell sectors/cells with antenna beamslooking toward the critical site/sector; and/or the neighbor cellsectors/sites which has high available resources.

In step 210, if no best neighbor site is found, then the previousrecommended configuration modifications are removed in step 204 and theoptimization process is ended in step 220. In the alternative, if nobest neighbor is found using the current criteria, then the searchcriteria for a best neighbor cell/sector could be modified or made moreflexible, for example, to determine neighbor cells/sectors with a lowernumber of handovers. Found best neighbor cells/sectors could be in thesame cell site/sector location or different location from the criticalcell site/sector. Additionally, there can be different priorities if theneighbor cell sectors/sites are in different cell site/sector locationthan for neighbor cell sectors/sites in same cell site/sector location.These priorities can be specified using a weighted metrics and thestatus of whether the neighbor cell sectors/sites is in the same ordifferent cell site/sector.

If a best neighbor site/or cell is found in step 210, then in step 211it is determined if the best neighbor cell has adequate availableresources for addressing the degraded condition. If the best neighborcell/sector does not have adequate available resources, then theprevious recommended configuration modifications are removed in step 204and the optimization process is ended in step 220. If the best neighborcell has adequate available resources for addressing the degradedcondition, then configuration modifications are calculated and added tothe modification queue in step 212 for application to the wirelessnetwork.

The calculated configuration modification could be that, for example,the critical cell site/sector antenna down tilt will be increased and/orthe critical cell site/sector transmitted power will be decreased; thecritical cell site/sector antenna pointing direction will be moved awayfrom the neighbor which has more available resources or away from aneighbor cell/sector which has less available resources; and/or thecritical cell site/sector antenna beamwidth will be decreased; and/orthe critical cell site/sector transmitted power will be decreased tocompensate for the increase in gain cased by decreasing beamwidth.

Additionally the calculated configuration modification could be that ,for example, that the best neighbor cell site/sector antenna down tiltwill be decreased and/or the best neighbor cell site/sector transmittedpower will be increased; the best neighbor cell site/sector antennapointing direction will be moved towards the critical cell site/sector;and/or the best neighbor cell site/sector antenna beamwidth will beincreased; and/or the best neighbor cell site/sector transmitted powerwill be increased to compensate for the decrease in gain cased byincreasing beamwidth. The recommendations above can be implementedsimultaneously or sequentially or with time delay in between or delayeduntil the next window is reached or until all delayed recommendationsare implemented.

Once the recommendation modifications are determined, the wirelessnetwork is monitored (as in step 201) to determine if the recommendationmodification address the degraded condition.

Exemplary Application

The following is an example of the method of optimizing a wirelessnetwork that is consistent the method described above with reference toFIG. 2.

-   -   1. The critical Hour is identified as Hour 9 (as expected from        the traffic model)    -   2. For cell 4 _(—)2, Hour 9, the available resources is below        the threshold; hence load balancing could help resolving it.    -   3. Best Neighbor search result is Cell 194 _(—)1    -   4. The Zone accumulated DCR is recorded (32.94) before        implementing any changes    -   5. Change Cell 4_(—)2 configuration as follows:        -   a. Increase the down tilt of the critical cell 4_(—)2 by 1            Deg        -   b. Decrease the Power By 1.5 dB    -   6. Monitor the performance for n days (In this case 5 days)    -   7. After n days, the 5 days accumulated DCR is enhanced as the        Zone accumulated DCR is changed from 32.94 to 32.601 and the        capacity have not degraded    -   8. Decrease the down tilt of the best neighbor 194_(—)1 by 1 deg    -   9. Monitor the performance for n days (In this case 5 days)    -   10. After n days, the 5 days accumulated DCR is found to be        degraded to be 32.675 However it is still below the original        accumulated DCR of 32.94    -   11. Best Neighbor search result is Cell 10_(—)3    -   12. Change Cell 4_(—)2 configuration as follows:        -   a. Increase the down tilt of the critical cell 4_(—)2 by 1            Deg        -   b. Decrease the Power By 1.5 dB    -   13. Monitor the performance for n days (In this case 5 days)    -   14. After n days, the 5 days accumulated DCR is enhanced as the        Zone accumulated DCR is changed to 31.962 and the capacity have        not degraded    -   15. Decrease the down tilt of the best neighbor 10_(—)3 by 1 deg    -   16. Monitor the performance for n days (In this case 5 days)    -   17. After n days, the 5 days accumulated DCR is enhanced to be        31.866    -   18. Repeat 11 to 14 and the 5 days accumulated DCR becomes        31.168    -   19. Repeat 15 to 17 and the 5 days accumulated DCR becomes        30.997    -   20. Now Cell 4_(—)2 has free available resources and load        balancing will not help in increasing the capacity of the        network.

FIG. 3 illustrates a method for determining a critical zone requiringoptimizing of network parameters in accordance with an embodiment of theinvention. In step 301, neighbor lists are collected for a criticalcell/sector. The neighbor list includes all the potential neighborcell/sectors for a particular a cell/sector, and it may include neighborpriorities as well. A potential neighbor cell/sector is a cell/sectorthat provides services to mobile equipment as part of a handoveroperation when the mobile equipment is traveling from one coverage areato another. The neighbor list can be stored in the network database 110.

The neighbor list can be stored in the network database 110 in the formof table that includes a list of cells and a corresponding list ofzones. For each critical cell site/sector needing optimization, a localzone will be identified as the set of the neighbor cell sites/sectorsbased on some criteria, which can also be based on one or moreperformance metrics. A “cells table” will be formed to contain all thecells in the local zones of all the critical cells/sectors, and it willcontain cell_id and simple_zone_id=local_zone_id for each cell. A“simple zone list” saves the checked/partially checked local zonesduring the search, and it contains the simple zone id and thecorresponding final zone. The “cells list” saves the checked/partiallychecked cells during the search, and it contains the cell_id and thecorresponding final zone.

In step 302, the cells table is sorted by simple zone_ID and then bycell_ID. Initially both the cells list and simple zone list are empty.For each entry in the cells table the following operation take place. Instep 303, an X zone reference is determined from the cell list based onfinding a cell_ID that matches the cell_ID entered for a cell. In step304, a Y zone reference is determined from the simple zone list based onfinding a zone_ID that matches the zone_ID entered for the cell. Oncethe X zone reference and Y zone reference are determined for thecritical cell, it then needs to be determined if the X zone referenceand the Y zone reference are included in a critical zone. In step 305,it is determined if the X zone reference is in a critical zone. If the Xzone reference is in a critical zone, then in step 306 it is determinedif the Y zone reference is in a critical zone. If both the X zonereference and the Y zone reference are included in a critical zone, thenin step 307 it is determined if the X zone reference and the Y zonereference refer to the same zone. If the X zone reference and the Y zonereference also refer to the same zone, then in step 308, the cell_ID isadded to this final critical zone. In step 309, it is determined if anycells in the cells table has been unchecked. If not, the process isended in step 320. If there are cells in the cells table that have notbeen checked, then the remaining cells in the cells table are checked byreturning to step 303.

In step 307, if the X zone reference and the Y zone reference arereferring to the different zones, then a new critical zone is created instep 310. In step 311, the X zone reference and the Y zone are includedin the new final critical zone, the cell list in the database 110 isupdated for the newly created zone (i.e., by cell_ID and zone_ID) andthe zone in the simple zone list is updated for the newly created zone.Also, in step 312 the previous zones for the X zone reference and the Yzone reference are removed. The process then returns to step 309 whereit is determined if any cells in the cells table has been unchecked. Ifnot, the process is ended in step 320. However, if there are cells inthe cells table that have not been checked, then the remaining cells inthe cells table are checked by returning to step 303.

In step 306, if it is determined that the X zone reference is in acritical zone, but the Y zone reference is not, then in step 313 it isdetermined that the X zone reference is the final critical zone, as insteps 314 and 308, the Y zone reference is added to the final criticalzone that includes X. The process then returns to step 309 where it isdetermined if any cells in the cells table has been unchecked. If not,the process is ended in step 320. However, if there are cells in thecells table that have not been checked, then the remaining cells in thecells table are checked by returning to step 303.

In step 305, if it is determined that the X zone reference is not in acritical zone then in step 315 it is determined if the Y zone referenceis in a critical zone. If it is determined that X zone reference is notin a critical zone, but the Y zone reference is in a critical zone, thenin step 316, it is determined that the Y zone reference is the finalcritical zone, as in steps 314 and 308, the X zone reference is added tothe final critical zone that includes the Y zone reference. The processthen returns to step 309 where it is determined if any cells in thecells table has been unchecked. If not, the process is ended in step320. However, if there are cells in the cells table that have not beenchecked, then the remaining cells in the cells table are checked byreturning to step 303.

In step 315, if it is determined that the X zone reference is not in acritical zone, and the Y zone reference is not in a critical zone, thenin step 317, a new critical zone is created that includes the X zonereference and the Y zone reference. Then in steps in steps 314 and 308,the IDs for the newly added zone are added to cell list and simple zonelist and the X zone reference and the Y zone reference are added to afinal critical zone. The process then returns to step 309 where it isdetermined if any cells in the cells table has been unchecked. If not,the process is ended in step 320. However, if there are cells in thecells table that have not been checked, then the remaining cells in thecells table are checked by returning to step 303.

FIG. 4 illustrates a method for determining a best neighbor cell inaccordance with an embodiment of the invention. As noted above, if acritical cell site/sector does not have adequate available resources,then it is important (for performing network optimization) to determineneighbor cell sites/sectors that can assisting in addressing anydegraded conditions

In step 401, the neighbor cells/sectors are determined based on thecells list table in the database 110. In step 402, the neighbor list issorted by network statistics. As noted above, network statistics mayinclude, but are not limited to, key performance Indicators (KPIs). Anexample of a KPI is the dropped calls rate or handovers, which is theratio between the failed calls and the total number of calls requested.The network statistics may also include, but are not limited to thefollowing:

Exemplary Switch Statistics

UL and DL Stats For Each Sector/Carrier: Load, Erlangs and Throughput

Capacity For Each Sector/Carrier

Sensitive KPIs To Operators Per Sector/Carrier Such as Dropped Calls andBlocked Calls

Location Of Most Users (Clusters)

Year/Month/Day/Time

Cell ID

Antenna ID

Carrier Frequency

Number Of Established Calls

Channel Elements (CE) Primary Use

% Primary Traffic CE Usage

% Secondary Traffic CE Usage

Total CE Usage (Erlang)

Peak # of Walsh Codes

Soft Handover Overhead %

Soft or hard handover counts

Peak DL Power

Number Of Dropped And Lost Calls

Number Of Blocked Calls

UL Thermal Noise Floor (main)

UL thermal Noise Floor (diversity)

Average DL Power

Pilot, Paging and Sync Channels Powers

Peak Number of Primary Walsh codes

Reported Or Calculated Sector Load For UL

Exemplary Network Parameters

Site Latitude And Longitude

Type: Macro-Cell, Micro-Cell, Repeater

Handoff Parameters (T_Add, T_Drop, Tt_Drop, T_Comp)

PA Output Power

Antenna Direction

Antenna Height Above Ground And Sea Level

Antenna Model, Azimuth BW, Elevation BW, Gain, Electrical And MechanicalTilt

PN Offset Per Sector

Morphology: Urban, Highway, Suburban, Rural, Dense Urban

Number Of RF Carriers Per Sector And Their Frequencies

Equipment Multi-Antenna Capability: Rx Diversity, STC, MIMO

Losses From PA Output To Antenna Ports If Applicable

Multi-Carriers To Antennas Mapping

Technology: WIMAX, UMTS, HSxPA, CDMA2000, 1xRTT, 1x-EVDO Rev. A, B or C,GSM, etc., And Supported Features By The Equipment

In step 403, the neighbor cells are then grouped based on availableresources and network statistics. The grouped neighbor cells are sortedbased on network statistics. Then, in step 404, the neighbor cells inthe first group are ranked based on their available resources. Forexample, the top neighbor cell sites/sectors may have a high number ofhandovers with the critical cell site/sector, or the top neighbor cellsites/sectors may have antenna beams looking toward the criticalsite/sector. In step 405 the best neighbor cells/sectors in the group isdetermined. In step 406, it is determined if the best neighbor cell hasadequate available resources to address the degraded condition. If not,then another best neighbor cell from the group is determined, as in step405, which has resources available to address the degraded condition.Once a best neighbor cell/sector is determined, then in step 407,recommended modifications to the wireless network are calculated. If thebest neighbor is not found, the next group will be searched using thesame criteria.

As noted above, the calculated configuration modification could be that,for example, the critical cell site/sector antenna down tilt will beincreased and/or the critical cell site/sector transmitted power will bedecreased; the critical cell site/sector antenna pointing direction willbe moved away from the neighbor which has more available resources oraway from a neighbor cell/sector which has less available resources;and/or the critical cell site/sector antenna beamwidth will bedecreased; and/or the critical cell site/sector transmitted power willbe decreased to compensate for the increase in gain cased by decreasingbeamwidth.

Additionally, the calculated configuration modification could be that,for example, that the best neighbor cell site/sector antenna down tiltwill be decreased and/or the best neighbor cell site/sector transmittedpower will be increased; the best neighbor cell site/sector antennapointing direction will be moved towards the critical cell site/sectorand/or the best neighbor cell site/sector antenna beamwidth will beincreased; and/or the best neighbor cell site/sector transmitted powerwill be increased to compensate for the decrease in gain cased byincreasing beamwidth. The recommendations above can be implementedsimultaneously or sequentially or with time delay in between.

FIG. 5 is a more detailed description of optimization apparatus 101 forperforming the method of self-optimization as previously described withreference to FIGS. 2-4. In FIG. 5, the optimization apparatus 101includes a memory 501, a processor 502, user interface 503, applicationprograms 504, communication interface 505, and bus 506.

The memory 501 can be computer-readable storage medium used to storeexecutable instructions, or computer program thereon. The memory 501 mayinclude a read-only memory (ROM), random access memory (RAM),programmable read-only memory (PROM), erasable programmable read-onlymemory (EPROM), a smart card, a subscriber identity module (SIM), or anyother medium from which a computing device can read executableinstructions or a computer program. The term “computer program” isintended to encompass an executable program that exists permanently ortemporarily on any computer-readable storage medium as described above.

The computer program is also intended to include an algorithm thatincludes executable instructions stored in the memory 501 that areexecutable by one or more processors 502, which may be facilitated byone or more of the application programs 504. The application programs504 may also include, but are not limited to, an operating system or anyspecial computer program that manages the relationship betweenapplication software and any suitable variety of hardware that helps tomake-up a computer system or computing environment of theself-optimization apparatus 501. General communication between thecomponents in the self-optimization apparatus 101 is provided via thebus 506. The self-optimization algorithm as described with reference toFIGS. 2-4 can be stored, for example, in the memory 501 of theself-optimization apparatus 101.

The user interface 503 allows for interaction between a user and theself-optimization apparatus 101. The user interface 503 may include akeypad, a keyboard, microphone, and/or speakers. The communicationinterface 505 provides for two-way data communications from theself-optimization apparatus 101. By way of example, the communicationinterface 505 may be a digital subscriber line (DSL) card or modem, anintegrated services digital network (ISDN) card, a cable modem, or atelephone modem to provide a data communication connection to acorresponding type of telephone line. As another example, communicationinterface 505 may be a local area network (LAN) card (e.g., forEthernet™ or an Asynchronous Transfer Model (ATM) network) to provide adata communication connection to a compatible LAN.

Further, the communication interface 505 may also include peripheralinterface devices, such as a Universal Serial Bus (USB) interface, aPersonal Computer Memory Card International Association (PCMCIA)interface, and the like. The communication interface 505 also allows theexchange of information across one or more wireless communicationnetworks. Such networks may include cellular or short-range, such asIEEE 802.11 wireless local area networks (WLANS). And, the exchange ofinformation may involve the transmission of radio frequency (RF) signalsthrough an antenna (not shown).

From the description provided herein, those skilled in the art arereadily able to combine software created as described with theappropriate general purpose or special purpose computer hardware forcarrying out the features of the invention.

Additionally, it should be understood that various changes andmodifications to the presently preferred embodiments described hereinwill be apparent to those skilled in the art. Such changes andmodifications can be made without departing from the spirit and scope ofthe present subject matter and without diminishing its intendedadvantages. It is therefore intended that such changes and modificationsbe covered by the appended claim.

1.-17. (canceled)
 18. A method, comprising: sending a plurality ofsignals to incrementally change a configuration of an antenna of awireless network, the plurality of signal including a first signal, asecond signal and a third signal, the second signal being sent after thefirst signal and before the third signal; and monitoring, for eachsignal from the plurality of signals, a performance metric value of thewireless network in response to that signal, the sending of the thirdsignal including selecting the configuration of the antenna for thethird signal based on a performance metric value for the first signal, aperformance metric value for the second signal and an operationalcondition associated with the performance metric.
 19. The method ofclaim 18, wherein: the configuration of the antenna for the third signalcorresponds to the configuration of the antenna for the first signalwhen the performance metric value for the second signal crosses theoperational condition.
 20. The method of claim 18, wherein: theconfiguration of the antenna for the third signal does not correspond tothe configuration of the antenna for the first signal and theconfiguration of the antenna for the second signal when the performancemetric value for the second signal does not cross the operationalcondition.
 21. The method of claim 18, wherein: the plurality of signalsincluding a fourth signal, the fourth signal is sent after the firstsignal, the second signal and the third signal, the configuration of theantenna for the fourth signal corresponds to the configuration of theantenna for the first signal when the performance metric value for thethird signal crosses the operational condition and when the performancemetric value for the first signal is better than the performance metricvalue for the second signal and the performance metric value for thethird signal.
 22. The method of claim 18, wherein: the plurality ofsignals including a fourth signal, the fourth signal is sent after thefirst signal, the second signal and the third signal, the configurationof the antenna for the fourth signal corresponds to the configuration ofthe antenna for the second signal when the performance metric value forthe third signal crosses the operational condition and when theperformance metric value for the second signal is better than theperformance metric value for the first signal and the performance metricvalue for the third signal.
 23. The method of claim 18, wherein themonitoring includes: receiving, for each signal from the plurality ofsignals, network data for the wireless network in response to thatsignal; calculating the performance metric value for that signal. 24.The method of claim 18, wherein the configuration of the antenna foreach signal from the plurality of signals is at least one of an antennatilt, an antenna power, an antenna direction or an antenna beamwidth.25. A non-transitory processor-readable medium storing code representinginstructions to be executed by a processor, the code comprising code tocause the processor to: send a first configuration parameter value to anantenna of a wireless network so that a configuration of the antennachanges based on the first configuration parameter value at a firsttime; send a second configuration parameter value to the antenna of thewireless network so that the configuration of the antenna changes basedon the second configuration parameter value at a second time after thefirst time; if a performance metric value of the wireless networkassociated with the second configuration parameter value crosses anoperational condition, send the first configuration parameter value tothe antenna of the wireless network so that the configuration of theantenna changes based on the first configuration parameter value at athird time after the second time; and if the performance metric value ofthe wireless network associated with the second configuration parametervalue does not cross the operational condition, send a thirdconfiguration parameter value to the antenna of the wireless network sothat the configuration of the antenna changes based on the thirdconfiguration parameter value at the third time.
 26. The non-transitoryprocessor-readable medium of claim 25, the code further comprising codeto cause the processor to: if a performance metric value of the wirelessnetwork associated with the third configuration parameter value crossesthe operational condition, perform the following: send the firstconfiguration parameter value to the antenna of the wireless network sothat the configuration of the antenna changes based on the firstconfiguration parameter value at a fourth time after the third time whenthe performance metric value associated with the first configurationparameter value is better than the performance metric value associatedwith the second configuration parameter value; and send the secondconfiguration parameter value to the antenna of the wireless network sothat the configuration of the antenna changes based on the secondconfiguration parameter value at the fourth time when the performancemetric value associated with the second configuration parameter value isbetter than the performance metric value associated with the firstconfiguration parameter value.
 27. The non-transitory processor-readablemedium of claim 25, wherein: the first configuration parameter valuerelates to a first parameter type, the second configuration parametervalue relates to a second parameter type different from the firstparameter type.
 28. The non-transitory processor-readable medium ofclaim 25, wherein: the first configuration parameter value relates to aparameter type, the second configuration parameter value relates to theparameter type.
 29. The non-transitory processor-readable medium ofclaim 25, wherein: the first configuration parameter value relates to afirst parameter type; the second configuration parameter value relatesto the first parameter type; the code to send the first configurationvalue includes code to send a third configuration value so that theconfiguration of the antenna changes based on the first configurationparameter value and the third configuration parameter value at the firsttime; the third configuration parameter value relates to a secondparameter type different from the first parameter type.
 30. Thenon-transitory processor-readable medium of claim 25, wherein: the firstconfiguration parameter value relates to a first parameter type; thesecond configuration parameter value relates to the first parametertype; the code to send the first configuration value includes code tosend a third configuration value so that the configuration of theantenna changes based on the first configuration parameter value and thethird configuration parameter value at the first time; the code to sendthe second configuration value includes code to send a fourthconfiguration value so that the configuration of the antenna changesbased on the second configuration parameter value and the fourthconfiguration parameter value at the second time; the thirdconfiguration parameter value and the fourth configuration parametervalue relate a second parameter type different from the first parametertype; the performance metric value of the wireless network associatedwith the second configuration parameter value is also associated withthe fourth configuration value.
 31. The non-transitoryprocessor-readable medium of claim 25, wherein the configuration of theantenna for each signal from the plurality of signals is at least one ofan antenna tilt, an antenna power, an antenna direction or an antennabeamwidth.
 32. A method, comprising: continuously optimizing, for aperiod of time, performance of a coverage area of a wireless networkbased on iteratively performing: sending a configuration parameter valuefor a current iteration to the wireless network; receiving, from thewireless network, network data for the coverage area based on theconfiguration parameter value for the current iteration; calculating aperformance metric value based on the network data associated with theconfiguration parameter value for the current iteration; and revertingthe wireless network to a configuration parameter value for a prioriteration when the performance metric value for the configurationparameter value for the current iteration crosses an operationalcondition.
 33. The method of claim 32, wherein: the configurationparameter value for the prior iteration is a prior configurationparameter value for a first prior iteration, a prior configurationparameter value for a second prior iteration is sent to the wirelessnetwork after the prior configuration parameter value for the firstprior iteration is sent to the wireless network and before theconfiguration parameter for the current iteration is sent to thewireless network, a performance metric value for the prior configurationparameter value for the second prior iteration is between a performancemetric value for the prior configuration parameter value for the firstprior iteration and the operational condition.
 34. The method of claim32, wherein the configuration parameter value for the current iterationis a first parameter type, the configuration parameter value for theprior iteration is a second parameter type different from the firstparameter type.
 35. The method of claim 32, wherein the configurationparameter value for the current iteration is to an antenna tilt value,the configuration parameter value for the prior iteration is an antennapower, an antenna direction or an antenna beamwidth.
 36. The method ofclaim 32, wherein the configuration parameter value for the currentiteration is a first antenna tilt value, the configuration parametervalue for the prior iteration is a second antenna tilt value differentfrom the first antenna tilt value.
 37. The method of claim 32, whereinthe configuration parameter value for the current iteration relates to aparameter type, the configuration parameter value for the prioriteration relates to the parameter type, the parameter type is at leastone of an antenna tilt, an antenna power, an antenna direction or anantenna beamwidth.